Senior Data Analytics Program Manager at Bitcot Technologies · Remote only · 5 - 10 years · ₹15L - ₹25L / yr · Profitable · Remote only · Posted 11 Feb 2026

Role Summary
Provide hands-on leadership across data and analytics initiatives, helping drive execution, coordination, and delivery in a fast-moving, evolving environment.
Key Responsibilities
• Partner closely with Data & Analytics leadership to translate priorities into executable plans.
• Drive delivery across cross-functional teams (data engineering, analytics, platform).
• Manage dependencies, risks, and timelines in a complex enterprise setting.
• Act as a trusted execution lead during periods of rapid change.
Key Skills
• Strong experience in data and analytics programs in large enterprises.
• Comfortable operating with ambiguity and evolving strategy.
• Excellent stakeholder communication and coordination skills.
• Prior healthcare or regulated-industry experience preferred.

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Job Title: Senior Data Analyst
Location: Sharnam Metrolinks, Amraiwadi, Ahmedabad
Working Days: 6 Days a Week
Department: MDO
Reporting To: COO
Employment Type: Full-Time
Job Summary
We are seeking a highly analytical and detail-oriented Senior Data Analyst to lead data management, reporting, automation, and system development initiatives across the organization.
The role focuses on transforming raw data into meaningful insights, designing and implementing automated systems, strengthening data structures, and supporting cross-functional teams with accurate, actionable intelligence to drive strategic and operational business decisions.
Key Responsibilities
1. Data Management & Reporting
● Collect, clean, validate, and consolidate data from multiple internal and external sources.
● Prepare and deliver daily, weekly, and monthly MIS reports for management and departments.
● Design, develop, and maintain dashboards to track KPIs, performance metrics, and operational trends.
2. Database & Data Accuracy Management
● Manage and regularly update internal databases, spreadsheets, and reporting systems.
● Ensure data accuracy, consistency, integrity, and confidentiality across all platforms.
● Implement best practices for data validation, version control, and audit checks.
3. Data Analysis & Business Insights
● Analyze large and complex datasets to identify trends, patterns, gaps, and anomalies.
● Translate data findings into clear, actionable insights and recommendations to support
strategic and operational decision-making.
4. Reporting Automation, System Recommendation & Implementation
● Identify opportunities to replace manual or semi-manual processes with automated, data-driven systems.
● Design and implement automated reporting frameworks, dashboards, and data pipelines using Excel (Power Query, VBA, Macros), SQL, BI tools, and Python.
● Proactively suggest new automation tools, system enhancements, or integrations to
improve efficiency, accuracy, and scalability.
● Lead the end-to-end implementation of approved automation initiatives, including requirement gathering, system design, testing, deployment, and stabilization.
● Continuously monitor and optimize automated systems in line with business growth and evolving data needs.
5. Cross-Functional Coordination & Support
● Collaborate with Sales, HR, Finance, Operations, and other departments to understand
reporting and data requirements.
● Provide support for ad-hoc analysis, custom reports, and special data requests.
● Act as a data partner to department heads for decision support and performance tracking.
6. Documentation & Compliance
● Maintain complete and updated documentation for MIS processes, reports, data models,
automation logic, and system changes.
● Ensure compliance with company data governance policies and applicable data protection standards.
System Development & Data Structuring Responsibilities
● Study and understand departmental workflows to evaluate how data is generated, processed, and utilized.
● Review existing manual and digital data systems to identify operational gaps, risks, and
mprovement opportunities.
● Recommend structured data models, reporting formats, and storage solutions aligned with
business requirements.
● Coordinate with department heads to define data structures, access levels, and reporting
standards.
● Implement new or upgraded data systems (Excel-based models, cloud platforms, ERP
integrations) with minimal operational disruption.
● Design structured data formats and role-based access controls to ensure secure and
organized data management.
● Train employees on newly implemented systems and provide post-implementation
support.
● Monitor system performance, resolve issues, and continuously improve systems based on
user feedback and organizational growth.
Qualifications & Experience
● Bachelor’s degree in Commerce, Statistics, Computer Applications, or a related field.
● 3–5 years of experience in data analytics, reporting, or system automation roles.
● Strong analytical thinking, logical reasoning, and problem-solving abilities.
● High attention to detail with excellent organizational and documentation skills.
Technical Skills (Must Have)
● Advanced Excel: Power Query, Power Pivot, VBA basics, Macros, Charts
● BI Tools: Power BI or Tableau (DAX, data modeling, dashboard optimization)
● Google Apps Script: Automation in Google Sheets, custom functions, triggers, API integrations, workflow optimization
● Vlook
Preferred Skills
● Strong verbal and written communication skills
● Ability to handle sensitive and confidential information responsibly
● Quick learner with a tech-savvy, improvement-driven, and solution-oriented mindset
We’re looking for a dynamic and driven Data Analyst to join our team of technology enthusiasts. This role is crucial in transforming data into insights that support strategic decision-making and innovation within the insurance technology (InsurTech) space. If you’re passionate about working with data, understanding systems, and delivering value through analytics, we’d love to hear from you.
What We’re Looking For
- Proven experience working as a Data Analyst or in a similar analytical role
- 5+ Years of experience in the field
- Strong command of SQL for querying and manipulating relational databases
- Experience with Power BI for building impactful dashboards and reports
- Familiarity with QlikView and Qlik Sense is a plus
- Ability to communicate findings clearly to technical and non-technical stakeholders
- Knowledge of Python or R for data manipulation is nice to have
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field
- Understanding of the insurance industry or InsurTech is a strong advantage
What You’ll Be Doing:
- Delivering timely and insightful reports to support strategic decision-making
- Working extensively with Policy Administration System (PAS) data to uncover patterns and trends
- Ensuring data accuracy and consistency across reports and systems
- Collaborating with clients, underwriters, and brokers to translate business needs into data solutions
- Organizing and structuring datasets, contributing to data engineering workflows and pipelines
- Producing analytics to support business development and market strategy

Bachelor’s degree in Engineering, Computer Science, or a related discipline
• 8+ years of experience in project or programme management
• 3+ years of experience delivering AI, Machine Learning, Data, or Analytics programmes
• PMP, Agile, Scrum, or equivalent certification preferred
About the company
We are an AI diffusion company. We partner with midmarket companies in asset-heavy, regulated industries to co-build deeply industry-specific agentic and machine learning solutions, which then get diffused across the industry through revenue-share and equity-linked models.
Our Past
We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.
Team
Our team of 20+ employees consists of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, UZH. Our team includes academicians, IBM Research Fellows, and former founders. This role focuses on healthcare and RCM, working alongside our AI/ML engineers, data scientists and domain specialists.
Key Responsibilities
- Lead product ideation, solution design, and technical strategy from concept to execution.
- Drive end-to-end product development, translating business needs into scalable technical solutions.
- Build and lead engineering teams to deliver high-impact products.
- Design and develop robust data systems to process and structure unorganized data from ERP/CRM platforms.
- Leverage AI and domain expertise in healthcare/RCM to build innovative solutions.
- Drive technology-led growth, with a focus on product scalability and business outcomes.
\Required Skills & Experience
- 15–20 years of experience in technology leadership, preferably as a CTO or senior technology leader.
- Proven experience building and/ or exiting startups.
- Strong expertise in data engineering, complex data systems, and unstructured data processing.
- Experience with AI-driven products, preferably in healthcare or Revenue Cycle Management (RCM).
- Strong product thinking, system design, architecture, and end-to-end execution capabilities.
- Ability to translate business requirements into technical roadmaps and scalable products.
Job Title: Chief of Staff (AI & Data-Driven Strategy)
Company: StarApps Studio
Experience: 4+ years
Location:Pune (On-site)
About StarApps Studio
StarApps Studio is a fast-growing Shopify app development company building high-impact ecommerce SaaS products for global merchants. We operate in a high-ownership, fast-execution environment where data, clarity, and speed matter.
Role Overview
We are looking for a highly analytical and operational Chief of Staff to serve as the right-hand strategic partner to our founders and leadership team. This role is a force multiplier—you will drive executive execution, improve high-level decision-making, and lead strategic initiatives across the company. This requires strong analytical thinking, AI fluency, and the operational rigor to turn visionary ideas into measurable results.
Key Responsibilities
- Executive Strategy & Alignment: Act as a strategic partner to founders by managing business priorities and driving key organizational deliverables.
- Cross-Functional Leadership: Own the execution of high-impact cross-functional initiatives across Product, Growth, Support, and Operations.
- Business Intelligence: Build dashboards, trackers, and comprehensive reports to empower data-backed leadership decision-making.
- AI & Operational Excellence: Leverage AI tools (ChatGPT, automation, analytics) to aggressively optimize workflows and scale internal productivity.
- Operating Rhythm: Drive the cadence of leadership by preparing strategic meeting agendas, synthesizing notes, and ensuring relentless closure on action items.
- Market & Product Strategy: Conduct deep-dive market, competitor, and product research within the Shopify and SaaS ecosystem to inform strategic direction.
- Stakeholder Management: Drive seamless communication and alignment between internal teams and external partners.
- Trusted Advisor: Maintain strict confidentiality and high ownership while handling ambiguous, complex business challenges.
Preferred Qualifications
- 3+ years of experience as a Chief of Staff, Strategy Consultant, or in a similar strategic role.
- Strong data-driven mindset with proven experience using Excel/Google Sheets, dashboards, and reporting tools.
- High proficiency with AI tools like ChatGPT, Notion AI, automation workflows, and prompt-based productivity.
- Exceptional written and verbal communication skills paired with strong stakeholder management abilities.
- Proven ability to operate in a fast-paced startup environment, taking high ownership of outcomes.
- Elite organizational skills, sharp attention to detail, and the ability to multitask seamlessly across competing priorities.
- Experience in ecommerce, SaaS, the Shopify ecosystem, or tech startups is a strong advantage.
- Comfortable working directly with founders and independently solving ambiguous, unstructured problems.
What We Offer
- Direct exposure to startup leadership and strategic decision-making.
- A high-impact role with a significant ownership and growth trajectory.
- The opportunity to work at the cutting-edge intersection of AI, ecommerce, and product execution.
- Competitive compensation with performance-driven growth opportunities.

Experience: 7–10+ years | Industry Preference: Financial Services / BFSI
Role Overview
We are seeking a Senior Reporting Analyst / Business Intelligence Lead to own and drive
enterprise reporting, analytics, and data insights across the organization. This is a senior,
hands-on role requiring deep technical expertise across the Microsoft data and BI stack,
strong business acumen, and the ability to operate with minimal hand-holding. The ideal
candidate will act as a bridge between business leadership and technical teams, translating
complex business questions into scalable, reliable data models and executive-ready insights.
Key Responsibilities
Serve as the primary owner of enterprise reporting and BI solutions, from data
ingestion through executive dashboards.
Design, build, and maintain scalable Power BI / Microsoft Fabric semantic models using
STAR schema best practices.
Partner closely with business stakeholders and C-level executives to define KPIs,
metrics, and reporting requirements.
Lead and present weekly reporting and insights sessions with senior and executive
leadership.
Ensure data accuracy, consistency, and trust across all reports and analytics outputs.
Proactively identify data quality issues, root causes, and remediation strategies.
Drive automation of reporting, alerts, and data refresh processes to reduce manual
effort.
Collaborate with engineering, data, and application teams to align business logic with
source system data structures.
Mentor junior analysts and establish BI standards, best practices, and documentation.
Technical Skills – Data & Backend
Advanced SQL: complex queries, views, stored procedures, and validation against
source systems (RDN, Recovery Connect).
Azure Data Factory: build and manage copy pipelines from SQL sources to data
warehouses / dedicated pools.
Incremental refresh, parameterized pipelines, and schema replication.
Data warehouse design: STAR schema, fact vs dimension tables, handling deleted
records and SCDs.
Technical Skills – Reporting & Frontend
Power BI / Microsoft Fabric: Power Query, DAX, and M language expertise.
Semantic model design (1-to-many, 1-to-1, many-to-1 relationships).
Query folding and performance optimization best practices.
Paginated Report Builder (SSRS-style) for automated Excel and PDF reporting.
Power Automate integration for alerts and workflow-driven notifications.
Data Quality & Analytics
Ability to clean, normalize, and reconcile data across multiple systems.
Strong troubleshooting skills when business definitions and data do not align.
Translate business terminology into accurate technical mappings and calculations.
Communication & Leadership
Serve as a key liaison between business stakeholders and technical teams.
Comfortable working directly with C-level executives and senior leadership.
Ability to lead executive-level meetings and clearly communicate insights.
Self-starter mindset with minimal hand-holding.
Qualifications
7–10+ years of experience in BI, analytics, or enterprise reporting roles.
Preferred experience in financial services or regulated environments.
Strong experience across the Microsoft BI ecosystem.
Preferred Certifications
Microsoft PL-300 (Power BI Data Analyst)
Microsoft DP-600 (Fabric Analytics Engineer)
Microsoft DP-700 (Fabric Data Engineer)
What Success Looks Like
Executive leadership trusts and relies on BI dashboards for decisions.
Reporting is automated, accurate, and scalable.
BI functions as a strategic partner to the business.
We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.
Qualifications and Skills:
- Minimum 5 years of experience as a Data Engineer
- Hands-on experience with Azure cloud-based data solutions
- Expertise in database design and management, including SQL databases such as SQL Server
- Proficient in ETL (Extract, Transform, Load) design for data integration and processing
- Strong knowledge of data modeling principles and techniques
- Ability to analyze and translate data into actionable insights, reports, and visualizations
- Proficiency in Power BI for reporting and data visualization
Desirable Skills:
- Experience with Power BI Report Builder / Reporting Services
- Knowledge of statistical analysis or Data Science
- Experience within the UK Insurance industry is a plus
- Python or R coding skills
Responsibilities:
- Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
- Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
- Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
- Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
- Implement different methods of streaming data and create reconciliations for datasets
- Build analytical models to support reporting and analytics
- Collaborate with an agile delivery team to work on the backlog of specified work
Sr. Data Engineer
Location: Pune
Responsibilities
· Lead the end-to-end design and development of scalable, high-performance data pipelines and ETL/ELT frameworks aligned with modern data engineering best practices.
· Architect complex data integration workflows that bring together structured, semi-structured, and unstructured data from both cloud and on-premise sources.
· Build robust real-time, batch, and on-demand pipelines with built-in observability—monitoring, alerting, and automated error handling.
· Partner with analysts, data scientists, and business leaders to define and deliver reliable data models, quality frameworks, and SLAs that power key business insights.
· Ensure optimal pipeline performance and throughput, with clearly defined SLAs and proactive alerting for data delivery or quality issues.
· Collaborate with platform, DevOps, and architecture teams to build secure, reusable, and CI/CD-enabled data workflows that align with enterprise architecture standards.
· Establish and enforce the best practices in source control, code reviews, testing automation, and continuous delivery for all data engineering components.
· Lead root cause analysis (RCA) and preventive maintenance for critical data failures, ensuring minimal business impact and continuous service improvement.
· Guide the team in establishing standards for data modeling, transformation logic, and governance, ensuring long-term maintainability and scalability.
· Design and execute comprehensive testing strategies—unit, integration, and system testing—ensuring high data reliability and pipeline resilience.
· Monitor and fine-tune data pipeline and query performance, optimizing for reliability, scalability, and cost-efficiency.
· Create and maintain detailed technical documentation, including data architecture diagrams, process flows, and integration specifications for internal and external stakeholders.
· Facilitate and lead discussions with business and operational teams to understand data requirements, prioritize initiatives, and drive data strategy forward.
Qualifications
· 7 to 10 years of hands-on experience in data engineering roles with a proven record of building scalable and secure data platforms.
· Over 5 years of experience in scripting languages such as Python for data processing, automation, and ETL development.
· 4+ years of experience with Snowflake, including performance tuning, security model design, and advanced SQL development.
· 5+ years of experience with data integration tools such as Azure Data Factory, Fivetran, or Matillion.
· 5+ years of experience in writing complex, highly optimized SQL queries on large datasets.
· Proven experience integrating and managing APIs, JSON, XML, and webhooks for data acquisition.
· Hands-on experience with cloud platforms (Azure/AWS) and orchestration tools like Apache Airflow or equivalent.
· Experience with CI/CD pipelines, automated testing, and code versioning tools (e.g., Git).
· Familiarity with dbt or similar transformation tools and best practices for modular transformation development.
· Exposure to data visualization tools like Power BI for supporting downstream analytics is a plus.
· Strong interpersonal and communication skills with the ability to lead discussions with technical and business stakeholders.
Education
Bachelor’s or Master’s degree in Computer Science/Information technology or related field.
Equivalent academic and work experience can be considered.
Strong Data Analyst Profile with Python, SQL, and data-pipeline expertise, ideally with retail / e-commerce datasets
2
Mandatory (Experience 1): Must have 4+ years of hands-on data-analyst experience, working with large datasets across areas such as sales, inventory, pricing, promotions, and customer behaviour.
3
Mandatory (Tech skill 1): Must have strong hands-on Python for data processing, transformation, automation, and analysis
4
Mandatory (Tech skill 2): Must have strong SQL skills, including complex queries, joins, aggregations, and data validation.
5
Mandatory (Tech skill 3): Must have a solid understanding of Data Lake architecture, ingestion, storage, and processing workflows
6
Mandatory (Tech skill 4): Must have hands-on experience with ETL / ELT pipelines, data integration, and transformation
7
Mandatory (Tech skill 5): Must have experience with Azure or GCP data services.
8
Mandatory (Tech skill 6): Must have understanding of or experience with Databricks and distributed data processing.
9
Mandatory (Tech skill 7): Must have knowledge of data modeling, data warehousing, and Lakehouse architecture
10
Mandatory (Tech skill 8): Must have experience with Power BI, Tableau, or Excel for reporting.
11
Mandatory (Communication): Must have strong analytical, documentation, and stakeholder-communication skills.
12
Mandatory (Education): Must hold a Bachelor’s degree in Computer Science, IT, Engineering, or a related field.
13
Mandatory (Note1): This is a 6-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)
1. Company Description:
Tatvic, is a marketing analytics company focusing on generating insights from data using long association with Google & its infrastructure. We breed,recognize and reward performance. As a company we are growing very fast & we are under transformation. To enable this transformation we need future leaders with eyesight which balances execution & strategic understanding.
Website: www.tatvic.com
2. Role Details
- Role: Lead Data Engineer
- Band: L4
- Department: Data Engineering
- Reporting to: L5 / Head of Delivery
- Location: Ahmedabad
- Job Type: Full Time
- Experience: 6-8 years of relevant experience
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.
3. Mission & Role Overview
- Mission: To create high-level organizational impact by leading a team to design and deliver scalable, high-performance cloud-native data solutions. The Lead Data Engineer (L4) is responsible for ensuring technical excellence—specifically in BigQuery optimization and secure GCP/AWS architectures—while driving the transition to Agentic AI workflows and creating value through the development of L1-L3 engineers.
- Role Overview: This is a pivotal leadership role on the Management Track, responsible for end-to-end data outcomes for the function. The Lead Engineer ensures the quality of engineering execution, manages team utilization and resource allocation, and serves as the primary technical representative in cross-functional forums with Marketing, Strategy, and Product teams.
4. Key Responsibilities
- Lead the design, development, and deployment of scalable and efficient cloud-based data pipelines and architectures.
- Build reusable data solutions and software components that serve multiple customers and use cases.
- Architect cloud environments using GCP, ensuring best practices in IAM, Security, and Networking.
- Conduct Exploratory Data Analysis (EDA) on clickstream and behavioral datasets to derive insights.
- Manage end-to-end ETL processes, including data extraction, transformation, and loading using Python, SQL, and Airflow.
- Design and build production-grade software (APIs, services, internal tools) with sound engineering practices — version control, testing, CI/CD, and code review.
- Extend data platforms with AI capabilities — integrating LLMs, RAG pipelines, and agentic workflows where they add clear business value.
- Perform Root Cause Analysis (RCA) and resolve data quality, pipeline, or application issues.
- Collaborate cross-functionally with Marketing, Insights, Product, and Engineering teams to align data initiatives with business goals.
- Document architectures, design decisions, and operations clearly and consistently.
- Coach and mentor team members, ensuring technical excellence and continuous learning.
- Participate in recruitment and knowledge-sharing through interviews, blogs, and webinars.
5. Must-Have & Good-to-Have Skills
Must-Have Skills:
- Strong understanding of clickstream data and data pipeline architecture
- Hands-on experience with cloud platforms (GCP)
- Expertise in SQL, Python, and Airflow
- Solid software engineering foundation — API design, testing, version control, and deployment practices
- Proven ability to perform exploratory data analysis and data validation
- Knowledge of cloud security, IAM, and networking best practices
- Working knowledge of building or integrating AI/LLM-based components into existing systems
- Excellent problem-solving, stakeholder management, and communication skills
Good-to-Have Skills:
- Certifications such as: Google Cloud Professional Data Engineer / Cloud Architect
- AWS Certified Data Analytics or Azure Data Engineer Associate
- Google Analytics 4 (GAIQ)
- Experience in marketing attribution, commerce data, or analytics ecosystems
- Exposure to cost optimization and cloud resource management
- Experience with agent frameworks (LangChain, ADK, MCP) or LLM APIs
- Experience building automation frameworks or internal data tools
6. Not-a-Fit Criteria
- Individual Contributor Focus: Operates as the team's best individual contributor instead of building team capability or empowering L3s.
- Information Hoarding: Keeps architectural patterns or tribal knowledge trapped in their head rather than creating reusable playbooks and documentation.
- Avoidance of Conflict: Avoids difficult performance conversations with underperforming team members, allowing capability gaps to persist.
- Activity Over Outcomes: Measures success by "tasks completed" rather than pipeline stability, data accuracy, or business impact.
- Functional Siloing: Fails to build partnerships with Marketing or Product teams, leading to misaligned data delivery.
Our Culture & Perks - Where Passion Meets Purpose:
- Competitive CTC: Based on experience and skillset
- Medical Insurance for you and your family
- Return-to-Work Program for New Moms — because career breaks shouldn’t break momentum
- 1 Work From Home Day/Month — flexibility when life calls
- 2 Birthday Leaves/Year — one for you, one for someone you love
- Monthly Engagement Activities — from game nights to learning sessions
- Inclusive Culture & Equal Opportunity Employer — diversity drives our innovation
- We Think Like Engineers & Athletes: we build, we iterate, we scale, we win — together
- 5-day workweek — because balance drives brilliance









